Machine Learning System Engineer
Shanghai, Shanghai, China
Operations and Supply Chain
Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Every single day, people do amazing things at Apple. Do you want to impact the future of ML for Manufacturing here at Apple by developing an extraordinary platform? This position involves a wide variety of skills, innovation, and is a rare opportunity to be working on ground breaking, new applications of machine learning, research and implementation. Ultimately, your work would have a huge impact on billions of users across the globe. You can help inspire change, by using your skills to influence globally recognized products' supply chain. The goal of Apple's Manufacturing and Operations team is to take a vision of a product and turn it into a reality. Through the use of statistics, the scientific process, and machine learning the team recommends and implements solutions to the most challenging problems. We’re looking for experienced machine learning professionals to help us revolutionize how we manufacture Apple’s amazing products. Put your experience to work in this highly visible role.
- Solid software development skills in one or more general purpose languages such as Python, Go, Swift/Objective-C, C/C++, adhering to the best coding practices.
- Experience in packaging and applying deep learning frameworks such as PyTorch/Torch, TensorFlow, Keras to real world applications that solve problems.
- Knowledge of validated approaches for scale-ability, productionalizing models and implementing machine learning applied to expansive and diverse datasets (storage, GPU, techniques for deep learning at scale).
- Experienced user of machine learning and statistical-analysis libraries, such as scikit-learn, NLTK, OpenCV, Pandas, SciPy, NumPy, Matplotlib, Tableau, etc.
- Knowledge of networking and communication concepts, such as TCP/IP, REST, RPC, etc.
- Experience with macOS and Linux operating systems, familiar with shell scripting.
- Experience of implementation and application of ML or Deep Learning solutions in real world problems is a plus.
- Experience with camera-based systems and image processing algorithms is a plus.
- Experience with mechanical system design and assembly is a plus.
- An inquisitive mindset and strong analytical skills for complex problem solving, and an aptitude for learning systems quickly.
- A proven track record for self-study and self-exploration into new tools and techniques
- Ability to explain and present analyses Machine Learning concepts to a broad technical audience.
- Good communication and collaboration skills.
- Fluent in both written and verbal English.
- Minimum 3 years of relevant experience.
As a member of the Product Operations Machine Learning team, you will be collaborating with teams across Apple to build and deploy machine learning platform and systems used in the mass production of all amazing Apple products. You will work with multi-functional teams to deploy our Machine Learning solutions to the massive Apple operations and supply chain, and help build the future of our smart manufacturing systems. Design and implementation of ML solutions, such as machine vision inspection for a wide range of prescriptive/predictive applications in dynamic production environments. Develop toolkits to guide application of machine learning systems combined with statistical tools for common engineers. Assemble large data sets for analysis either through direct SQL-based querying or development of scripts and code-modules to collate distributed and disparate data sources. Develops software components in Python, and/or Swift/Objective-C, Go, C/C++ towards roll-out of a data automation system qualifications. Adapt/customize hardware and software components for successful integration. Hands-on implementation and deployment of test software and hardware equipment in a factory environment. Carry out end-to-end prototyping and proof-of-concept tasks for new system ideas, involving mechanical design/assembly, software development and integration of subcomponents into a system. Work directly with system integration vendors and suppliers to turn prototypes into scalable production systems. Seek opportunities in the production and development processes to utilize computer vision, deep learning, algorithms and other ML tools for improvements.
Education & Experience
Master in Computer Science, Math, Statistics, Physics, Mechanical, Engineering or related level of experience required.